chank@cb.ecn.purdue.edu (King Chan) (10/05/90)
Greetings,
I would like propose two neural network questions. Perhaps someone
can give me some insight as to their solution.
I. Input Representation for Variable Length Data
It appears that most nn inputs are of fixed length (i.e
the number of input neurons are static). However, there
are cases where this is not applicable. For instance, a 2-D
connection table representation of chemical structure will
vary in size depending on the molecule. Is there a way to
get around this ?
II. Functional Relationship Training with Missing Data
Has there been any work on NN training and recall when
all the input and/or output node information is unavailable.
It appears to me that a value of 0 for an unknown attribute
value is insufficient. Any Comments ?
I hope these questions merit some discussion.
Thank you very much.
chank@cn.ecn.purdue